Pre-operative magnetic resonance imaging can predict prostate cancer with risk for positive surgical margins

M Quentin1, L Schimmöller2, T Ullrich1

  • 1Medical Faculty, Department of Diagnostic and Interventional Radiology, University Dusseldorf, Moorenstr. 5, 40225, Dusseldorf, Germany.

Abstract

Insights

Pre-operative 3 Tesla multiparametric prostate MRI (mpMRI) can predict positive surgical margins (PSM) during robotic assisted radical prostatectomy (RPE). Length of capsular tumor contact (LCC) and distance to the membranous urethra (UD) are key MRI predictors for PSM.

Area of Science:

  • Radiology
  • Urology
  • Oncology

Background:

  • Positive surgical margins (PSM) are a concern in radical prostatectomy.
  • Accurate pre-operative prediction of PSM can guide surgical planning and improve outcomes.

Purpose of the Study:

  • To identify reliable MRI-based predictors of PSM in patients undergoing robotic assisted radical prostatectomy (RPE).
  • To analyze the utility of 3 Tesla multiparametric prostate MRI (mpMRI) in predicting PSM.
  • To correlate specific MRI findings with the localization of PSM.

Main Methods:

  • Retrospective analysis of 179 patients who underwent 3T mpMRI and RPE.
  • Comparison of clinical and MRI parameters, including length of capsular tumor contact (LCC) and distance to membranous urethra (UD).
  • Evaluation of MRI visibility of prostate cancer (PCA) at PSM sites.

Main Results:

  • 27% of patients had PSM, predominantly at the capsule (apical/posterior) and apical urethra.
  • Prostate cancer (PCA) was visible on mpMRI at PSM sites in 93% (capsule) and 80% (urethra).
  • LCC (AUC 0.710), extraprostatic extension (EPE) (AUC 0.693), and UD (1-AUC 0.673) predicted overall PSM. UD ≤ 3.5 mm accurately predicted urethral PSM (95%), and LCC ≥ 22.5 mm predicted capsular PSM (77%).

Conclusions:

  • PSM commonly occur at the capsule (apex/posterior) and apical urethra.
  • LCC and UD are significant MRI predictors for PSM at specific locations.
  • Pre-operative mpMRI parameters can help identify prostate cancer (PCA) localizations at risk for PSM.